Advanced planning system transformation

Modernizing Supply Chain Planning for a Global Hard Goods Manufacturer

A global hard goods client partnering with McKinsey embarked on a 56-week end-to-end supply chain transformation, redesigning their planning processes and fully configuring their underutilized SAP IBP technology with cross-functional alignment across commercial, IT, and finance teams from day one.

The program overhauled the client's planning model—reducing SKU complexity by 30%, shifting inventory allocation decisions from 4-month-old data to near real-time (2-week) information, and embedding new capabilities across the organization through a rigorous change management effort.

The result was a dramatic 50% reduction in inventory, a 75% faster response time to market demand changes, and a 50% faster time-to-impact compared to a traditional APS implementation.

Scaling Agentic AI Across a Global Hardware Supply Chain

A large hardware original equipment manufacturer (OEM) partnered with McKinsey to design and implement an autonomous supply chain, leveraging agentic AI to transform its end-to-end operations.

The team established a comprehensive AI operating system built upon a new data product architecture that unified over 70 sources. Using an agile playbook, the program deployed agent-augmented workflows, starting with inbound and outbound logistics to ensure a self-funding model after six months before scaling toward fully autonomous processes.

The transformation delivered more than $600 million in realized impact, a 10x faster planning cycle, a 50% reduction in aged inventory costs, and a 5% decrease in procurement expenses.